Reinforcement Learning with Convex Constraints
NeurIPS, pp. 14070-14079, 2019.
In standard reinforcement learning (RL), a learning agent seeks to optimize the overall reward. However, many key aspects of a desired behavior are more naturally expressed as constraints. For instance, the designer may want to limit the use of unsafe actions, increase the diversity of trajectories to enable exploration, or approximate ex...More
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